Package: drjacoby 1.5.4
drjacoby: Flexible Markov Chain Monte Carlo via Reparameterization
drjacoby is an R package for performing Bayesian inference via Markov chain monte carlo (MCMC). In addition to being highly flexible it implements some advanced techniques that can improve mixing in tricky situations.
Authors:
drjacoby_1.5.4.tar.gz
drjacoby_1.5.4.zip(r-4.5)drjacoby_1.5.4.zip(r-4.4)drjacoby_1.5.4.zip(r-4.3)
drjacoby_1.5.4.tgz(r-4.4-x86_64)drjacoby_1.5.4.tgz(r-4.4-arm64)drjacoby_1.5.4.tgz(r-4.3-x86_64)drjacoby_1.5.4.tgz(r-4.3-arm64)
drjacoby_1.5.4.tar.gz(r-4.5-noble)drjacoby_1.5.4.tar.gz(r-4.4-noble)
drjacoby_1.5.4.tgz(r-4.4-emscripten)drjacoby_1.5.4.tgz(r-4.3-emscripten)
drjacoby.pdf |drjacoby.html✨
drjacoby/json (API)
# Install 'drjacoby' in R: |
install.packages('drjacoby', repos = c('https://mrc-ide.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mrc-ide/drjacoby/issues
- population_data - Population data.
Last updated 5 months agofrom:edfea6339e (on master). Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 24 2024 |
R-4.5-win-x86_64 | OK | Oct 24 2024 |
R-4.5-linux-x86_64 | OK | Oct 24 2024 |
R-4.4-win-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-aarch64 | OK | Oct 24 2024 |
R-4.3-win-x86_64 | OK | Oct 24 2024 |
R-4.3-mac-x86_64 | OK | Oct 24 2024 |
R-4.3-mac-aarch64 | OK | Oct 24 2024 |
Exports:check_drjacoby_loadedcpp_templatedefine_paramsplot_autocorrelationplot_cor_matplot_credibleplot_densityplot_mc_acceptanceplot_pairsplot_rung_loglikeplot_scatterplot_tracerun_mcmcsample_chains
Dependencies:askpassclicliprcodacolorspacecowplotcpp11crayoncredentialscurldescdplyrfansifarverforcatsfsgenericsgertGGallyggplot2ggstatsghgitcredsgluegtablehmshttr2iniisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeopensslpatchworkpillarpkgconfigplyrprettyunitsprogresspurrrR6rappdirsRColorBrewerRcpprlangrprojrootrstudioapiscalesstringistringrsystibbletidyrtidyselectusethisutf8vctrsviridisLitewhiskerwithryamlzip
Basic Example
Rendered fromexample.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2019-05-03
Double well
Rendered fromchecks_double_well.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2021-09-08
Getting Model Fits
Rendered fromgetting_model_fits.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2022-02-10
Installing drjacoby
Rendered frominstallation.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2019-05-02
Multilevel example with blocks
Rendered fromchecks_multilevel_blocks.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2021-09-08
Started: 2021-09-08
Normal model
Rendered fromchecks_normal_model.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2021-09-08
Started: 2021-09-08
Parallel Tempering
Rendered frommetropolis_coupling.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2019-05-22
Return prior
Rendered fromchecks_return_prior.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2021-09-08
Started: 2021-09-08
Running in Parallel
Rendered fromparallel.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2024-06-26
Started: 2019-05-22
Using Likelihood Blocks
Rendered fromblocks.Rmd
usingknitr::rmarkdown
on Oct 24 2024.Last update: 2022-02-10
Started: 2021-01-08
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Estimate autocorrelation | acf_data |
Check that drjacoby package has loaded successfully | check_drjacoby_loaded |
Create template for cpp | cpp_template |
Define parameters dataframe | define_params |
Flexible Markov Chain Monte Carlo via Reparameterization | drjacoby |
Gelman-Rubin statistic | gelman_rubin |
Plot autocorrelation | plot_autocorrelation |
Plot posterior correlation matrix | plot_cor_mat |
Plot 95% credible intervals | plot_credible |
Produce density plots | plot_density |
Plot Metropolis coupling acceptance rates | plot_mc_acceptance |
Produce scatterplots between multiple parameters | plot_pairs |
Plot loglikelihood 95% credible intervals | plot_rung_loglike |
Produce bivariate scatterplot | plot_scatter |
Plot parameter trace | plot_trace |
Population data. | population_data |
Run drjacoby MCMC | run_mcmc |
Sample posterior draws from all available chains | sample_chains |